a. Spatio-temporal distribution modeling using Gaussian Markov Random Field and its application (Toshihide Kitakado) b.Risk assessment of the domestic establishment of Chinese mitten crab using a multispecies simultaneous species distribution model (Kenji Yokota) c.Application to local-scale resource assessment and management using spatio-temporal distribution modeling (Shigehide Iwata) d.Construction of highly accurate nitrate profile data in the ocean (Fuminori Hashihama, Takehiro Nagai, Kohei Mizobata, Naho Miyazaki) e.System development of self-supervised contrast learning method as a basis for AI analysis of marine big data (Tomoyuki Takenawa) f. Investigation of reproducibility of spatio-temporal evolution model obtained by AI learning (Junichiro Tahara, Kengo Nakai) g.Construction of a red tide monitoring system based on citizen science (Toshiya Katano) Goal of this project Development of infrastructure and environment for the Integrated Fisheries Support System, which utilizes ocean-related big data, including environmental information and fisheries management and economic information. Acquisition, analysis with AI (Midori Kawabe, Saoba Rou, Naotomo Nakahara, Takero Yoshida) XNUMX <Distribution of marine products> XNUMX <Issues in the marine field> Establishment of AI analysis methods for solving the following problems XNUMX <Market price Trends> Construction of an integrated database of market prices and social big data and AI analysis (Taro Oishi) XNUMX <Aquaculture> Acquisition of data related to aquaculture of marine products and analysis with AI (Hidehiro Kondo, Ikuo Hirono, Keiichiro Koiwai) )XNUMX.Acquisition of marine big data and promotion of AI analysis research (XNUMX) Development of a fishery integrated support system that realizes resilient and sustainable fisheries using marine organism big data and training of marine AI human resources
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